Analytics as a Service
Demand Forecasting
Table of Contents
Definition
Problems Solved
- Restricted budgets
- High or unbalanced inventory levels
- Risk of being in a lengthy contract
- Attracting and retaining the right talent (data scientists)
- Unable to accurately plan merchandise allocation/replenishment (as a whole or per location)
- Time consuming when having to change plans due to unexpected events (low sales, weather etc.)
Relevant Roles
Detailed Description
Retailers are under unprecedented pressure to plan and execute inventory across the business in a rapidly changing environment. Forecasting consumer demand is a key step in anticipating inventory need in the business.
Building an accurate consumer demand forecast is not easy however, especially when historical data has little similarity to demand impacted by COVID lockdowns. If forecasting is produced based in 2018 and 2019 historical data, it is important to heavily factor in 2020 and 2021 since historical sales profile curves will likely look radically different from 2019 to 2020 due to the dramatic impact of COVID lockdowns on retail results world-wide.
Success Stories
Discover the power of Analytics as a Service in retail and how it unlocks data-driven success and empowers decision-making.
Optimize profits and inventory with our revolutionary Markdown Profit Maximizer Solution. Make informed decisions for optimal results!
Navigate uncertainty with confidence! Discover how our Demand Forecasting solution tackles the modern day challenges.
Discover the latest trends in demand forecasting and their potential impact on the future of businesses and how big companies use them.
Accurately predicting demand is crucial for retailers. In this blog post, we explore the consequences of inaccurate demand forecasting, the benefits of accurate forecasting, and the importance of using a demand forecast service.
Through a real-life example we have shown, how choosing our markdown solution can maximize profit and clear unwanted stock.